A high-resolution emissions inventory and its spatiotemporal pattern variations for heavy-duty diesel trucks in Beijing, China

Abstract

Heavy-duty diesel trucks (HDDTs) cause serious pollution, and a high spatiotemporal resolution emissions inventory is a valuable assessment tool for use in quantitatively understanding the emissions mechanisms of HDDTs and scientifically developing associated emissions reduction measures. This study aims to comprehensively utilize multi-source spatiotemporal data on transportation—including fine-scale trajectories of HDDTs, road traffic conditions, and attribute data for road networks and HDDTs—supplemented by relatively mature vehicle pollution emissions models to establish a high spatiotemporal resolution emissions inventory for HDDTs in Beijing using a bottom-up approach. Spatial statistical techniques, including spatial autocorrelation, high/low clustering, and outlier analysis, are also used to explore the spatiotemporal distribution pattern of pollution emissions in the city. The results showed the following: (1) spatially, nitrogen oxide (NOx) and particulate matter (PM) emission hotspots spread from the Beijing sixth-ring roads to the fourth-ring roads from daytime to nighttime. The road segments with high emissions intensities have pronounced spatial agglomeration effects at night, but these are scattered during daytime. (2) Temporally, total HDDT NOx emissions are consistent with the traffic volume trends and are lower during major festivals. The highest NOx emissions occur at intercity highways, and this reflects the severe impact that intercity freight traffic has on air quality. The dominant HDDT NOx emissions are from vehicles belonging to the China 4 emissions standard. (3) NOx and PM emissions have a significant spatial autocorrelation and exhibit high-value clustering as a whole. (4) At different time intervals, the distribution of High-High/Low-Low clustering and outliers of NOx and PM in the road network is consistent with the spatial distribution of the pollutant emission intensity. The High-Low outlier is mainly distributed within the fourth-ring roads, and the number gradually reduces between night and day. The Low-High outlier is affected by the heterogeneous distribution of HDDTs and exhibits discontinuous distribution characteristics. Our results effectively evaluate Beijing’s emissions control measures for HDDTs and provide a scientific decision-making basis for developing targeted emission reduction strategies for HDDTs.